network optimization presentation generic dec18

Fracton TechnologiesThe Cellular Symphony!

Innovative Solutions for Network Optimization

Authorized Partner

▪ A privately held company, headquartered in India

▪ Focused on innovations in RAN Optimization for GSM, UMTS & LTE Technologies

▪ Outstanding track record in offering Optimization Services to the leading operators

▪ Proud winner of 2015 Graham Bell Award for Best Telecom Product

About Us

The Company

The Team

▪ The team possesses world class expertise in –

▪ Planning & Management of Mobile Networks

▪ Design & Development of Telecom Products

▪ A fairly young, motivated and highly agile team

Strictly Confidential 2

Network Service Offerings


GSM/UMTS/LTE Network Parametric Optimization

Radio Access Network Audit

Automatic Frequency Planning

Spectrum

Re-farming

Wide Range of Services offered by Fracton effectively addresses the challenges faced by Mobile Operators!

RAN Challenges faced by MNOs


Inability to extract themaximum out of theinstalled RAN assetsdue to a number offactors!

RAN Asset Utilization

Improving KPI performance & fulfilling Regulator requirements on KPI Targets!

Improving KPIs

Customer has turned more Quality Conscious – Quality Differentiation is Vital!

Enhancing Customer

Experiences

Frequency Planning requirements are becoming more and more stringent due to reducing available spectrum on GSM!

Frequency Planning

RAN Challenges faced by MNOs (Cntd.)


Carving out sizablechunk of spectrumwhile minimizing theimpact on QoS/QoEfor GSM traffic is amassive challenge!

Spectrum Refarming

Reliable & seamless QoE. Tackling complicated traffic planning & Interference Management is crucial for extracting the value of today’s Heterogeneous Landscape!

HetNetLandscape

Efficient traffic balancing & offloading to intra /inter technologies is crucial for handling exponential traffic increase!

Increased Data Traffic

Challenge

Widespread small cell deployment is the need of the hour but comes with a range of unique challenges!

Small Cell Integration

The Enabler!

MaxCell – Introduction

Spectrum

Refarming

Parametric

Optimization

Network

Consolidation

MaxCell – Core Philosophy

Each Cell is Unique!

So are each of its neighbor relationships!

Why to condemn them to a herd culture, then?

By leaving their critical parameters at their default levels!

Respect their individuality, instead!

Give them what they ask for… and allow your

network to perform at its best!


Parametric Optimization

▪ An OSS based RAN Optimization Tool

▪ Addresses the Uniqueness of each Cell &

Neighbour

▪ Optimizes Network Performance & Quality of

Experience in a Flash!✓ Reduction in Customer Complaints

✓ Reduction in Call Drops

✓ Improvement in Voice Quality

✓ Reduction in Handover Failures

✓ Reduction in iRAT Handover Failures

✓ Improvement in Data Throughput

▪ Enables a Dynamic & Continuous Network

Optimization Regime

▪ Significant Capex & Opex Reduction

▪ Multi-vendor, Multi-technology Solution

MaxCell – Parametric Optimization


Pre-Post KPI

Reports

OSS/NMS

Operator’s Configuration

Management

System

Operator’s Performance

Management

System

Performance Data

Existing Configuration

MR/Trace Data/ Traffic Recordings

Recommended Configuration

Traditional Way

Default Cell DB ParametersSet at Network Level

No Performance Gains

Manual Way

Optimized Cell DB Parameters on RNC/BSC or Cluster Level

Marginal Performance Gains

Automated Way

MaxCell Optimizes Per Cell/Per Neighbor Cell DB Parameters

Decisions Based on Radio Network Configuration & Performance Counters, KPIs & MRR Reports

Significant Performance Gains


Why MaxCell ?

Automated Way of Cell Database Parameters Tuning


MaxCell Solution is Based on Iterative Parameters Tuning Cycles

MaxCell 4G Optimization Cycle

MaxCell Inputs

Optimization Targets

Optimization Engine

Parameters Implementation

Performance Assessment

RSRP & Ant Para

Optimization

•Coverage Optimization

•No Dominance Optimization

•Pilot Pollution Optimization

•SINR & CQI Optimization

RF Performan

ce Optimizati

on

•Intra/Inter Frequency Cell Re-selection

•Inter RAT Cell Re-selection

•Inter RAT & Inter Frequency HO

•Intra Frequency HO Parameters

•DL & UL Throughput

LTE Key Features

•Carrier Aggregation

•MIMO

•CSFB & SRVCC

•HetNet – Small Cells

Neighbor List

•PCI Optimization

•Intra & Inter Frequency Neighbor Lists

•IRAT Neighbor Lists


Typical Project Schedule – Improvements Observed in a Fortnight

MaxCell 4G Optimization Timelines

Week 1

•Selection of Optimization Area

•Existing Performance & KPI Assessment

•Define Optimization Targets – SINR, CQI, Layers Re-selection Criteria

•Schedule Traffic Recordings – MR & CQI

Week 2

•Import Network Configuration

•Import CM, PM & MR/Trace Recordings Data

•Run MaxCell Optimizer

•Generate Antenna Conf. & Cell Database Parameters Tuning Recommendations

Week 3-4

•Iteration 1a: Ant Conf & RSRP Power.

•Performance Data Collection for Iterations 1b, 1c & 1d – MR/Trace

•Iteration 1b: Intra Frequency & Inter RAT Cell Re-selection & HO Optimization

•Iteration 1c: Inter, Intra & Inter RAT Neighbor Lists Optimization

•Iteration 1d: Throughput DL & UL, Capacity, Features like MIMO, SRVCC, CSFB etc.

•Performance Data Collection for 2nd Iteration – MR/Trace & Counters

•Iteration 2 (Fine Tuning): Recommendations Generation & Implementation

Week 5

•Pre Post Performance Assessment

•Benchmarking

•Project Report Submission

MaxCell 4G Solution for ZTEData Input Requirements

• Configuration Dump– OSS XML Dump taken through OSS

Common Explorer

• Performance Counters & KPIs– OSS Counter Cell, Frequency Level & Per

Neighbour Level Stats

– 7 Working Days from 10 am to 10 pm

– NBH & BBH KPI Reports

• NetMax MR/CTS Recording– MR Recordings/Traces

• 3 Days & Hourly recordings from 11:00 am to 12:00 pm

Optimization Strategy: Exploiting Performance Counters & NetMax Recordings for

Assessing Traffic behavior which forms the basis for Optimization Algorithms.

MaxCell 4G Solution for NokiaData Input Requirements


Common Explorer





• Megamon-Emil Recording– Layer 3 Cell Trace Recordings


Optimization Strategy: Exploiting Performance Counters & Megamon Recordings for

Assessing Traffic behavior which forms the basis for Optimization Algorithms.

MaxCell 4G Solution for HuaweiData Input Requirements

• Configuration Dump– CME Configuration Dump taken

through OSS


Neighbour Level Stats– 7 Working Days from 10 am to 10 pm– NBH & BBH KPI Reports

• Huawei LTE Call Trace / CHR Recording– Layer 3 Cell Trace Recordings


Optimization Strategy: Exploiting Performance Counters & Traces Recordings for

Assessing Traffic & Inter Cell behavior which forms the basis for Optimization Algorithms.

MaxCell 4G Solution for EricssonData Input Requirements


Common Explorer





• Ericsson LTE CTR Recordings– Layer-3 Trace Recordings


Optimization Strategy: Exploiting Performance Counters & Cell Trace Recordings for





MaxCell Inputs


Optimization Engine



CPICH & Ant Para

Optimization

•Coverage Optimization

•Pilot Pollution

•No Dominance Areas Optimization

Soft Handovers

•Cell Selection/ReSelection – Intra/Inter Freq

•Soft Handovers Parameters Optimization

•IRAT Cell Reselection & HO Optimization

•Inter Frequency HO Settings

Capacity & Admission

Control

•AC Thresholds

•Max Power Per Link / FACH Power

•HSDPA & DL Power

•Code Allocation

Neighbor List

•Scrambling Code Optimization

•Intra & Inter Frequency Neighbor Lists

•IRAT Neighbor Lists




Week 1



•Define Optimization Targets – Voice Vs HSDPA

•Schedule Traffic Recordings – MR/Traces/Traffic Recording

Week 2


•Import CM, PM & Traffic Recordings Data


•Generate Antenna Conf. & Cell Database Parameter Recommendations

Week 3-4

•Iteration 1a: Ant Conf & CPICH Power.

•Performance Data Collection for Iterations 1b, 1c & 1d – MR/Traces/Traffic Recording

•Iteration 1b: Soft Handover, Inter Frequency & Inter RAT Performance Optimization

•Iteration 1c: Downlink/Uplink Capacity, HSDPA, Throughput Optimization

•Iteration 1d: Idle Mode & Neighbor List Optimization

•Performance Data Collection for 2nd Iteration – MR/Traces/Traffic Recording


Week 5


•Benchmarking


MaxCell 3G Solution for ZTEData Input Requirements






• ZTE MR/CDT/Call Trace System (CTS)– MR/Layer 3 Cell Trace Recordings


Optimization Strategy: Exploiting Performance Counters & Trace Recordings for


MaxCell 3G Solution for NokiaData Input Requirements


Common Explorer


Neighbour Level Stats– 7 Working Days from 10 am to 10 pm– NBH & BBH KPI Reports

• Megamon-Emil /CHR / MR Recordings– Layer 3 Cell Trace Recordings


Optimization Strategy: Exploiting Performance Counters & Megamon Recordings for


MaxCell 3G Solution for HuaweiData Input Requirements

• Configuration Dump– CME Configuration Dump taken

through OSS





• Huawei CHR / PCHR Recording– Layer 3 Cell Trace Recordings


Optimization Strategy: Exploiting Performance Counters & Trace Recordings for


MaxCell 3G Solution for EricssonData Input Requirements


Common Explorer

• Performance Counters & KPIs– OSS Path:

/var/opt/ericsson/nms_umts_pms_seg/segment1/XML/– Counter Cell Level Data & Per Neighbor Level– 7 Working Days from 10 am to 10 pm– MO Classes: UtranCell, RncFunction, Hsdsch, Handover,

UtranRelation, GsmRelation– NBH & BBH KPI Reports

• GPEH Traffic Recording– WMRR & WNCS Recordings– GPEH data for RNC with filter

“RRC_Measurement_Reports”• 3 Days Hours Data from 11:00 am to 12:00 pm

Optimization Strategy: Exploiting Performance Counters & GPEH Traffic Recordings for





MaxCell Inputs


Optimization Engine



Frequency Fine Tuning

•RF Path Issues

•Interference Reduction

•Overshooting Cells Optimization

Handovers

•Handovers Parameters Optimization

•Neighbor List Optimization

•QOS Features Optimization

Traffic Balancing/

Capacity

•Dual Band Layers

•Traffic Balancing / Capacity

•QOS Features Optimization

•Hierarchical / IBC Cells Opt

Power Control

•Power Control Parameters Opt

•Interference Control




Week 1



•Define Optimization Targets – DCR, Voice Quality & HOSR

•Schedule Traffic Recordings – MR / Traffic Recording

Week 2


•Import CM, PM & Traffic Recordings Data


•Generate Cell Database Parameter Recommendations

Week 3-4

•Iteration 1a: Freq Plan Fine Tuning & Neighbor List Tuning

•Performance Data Collection for Iterations 1b & 1c – In case Freq Plan Tuning is req.

•Iteration 1b: Traffic Balancing; Capacity Optimization; Dual Band Layers Opt

•Iteration 1c: Handover Performance, Power Control & QOS Features Optimization

•Performance Data Collection for 2nd Iteration – MR/Traffic Recordings & Counters


Week 5


•Benchmarking


Spectrum Refarming


Spectrum Refarming- Challenges & Task

Complex Network Transformation

RF Redesign – Coverage & Capacity

Multiple AFP Implementations

Traffic Balancing Between Layers

Cell Database Parameters Tuning

Spectral Efficiency

User Perceived Quality Improvement

Quality

• Spectral Efficiency & Frequency Plan Approach

• Activation of QOS Enhancement Features

• Cell Database Parameters Tuning

Capacity

• Traffic Dimensioning on New Spectrum

• Offloading Traffic towards Different Technologies

• TRX Dimensioning

Coverage

Identify Coverage Deficient Areas & Recommendations

Spectrum Refarming Steps

• BSS Configuration Audit & Scenarios Identification– Analysis of Existing Radio Network Configuration– Identification of Different Spectrum Re-farming Scenarios

• Site Configurations – Underlay/Overlay; Band Segregation between BCCH/TCH• TRX Dimensioning• AMR HR Usage Thresholds• Traffic Sharing with LTE/UMTS• Traffic Handling Capacity / Utilization

• Measurement Reports Recordings– MR Data Collection for 2-3 Days on Existing Network – Creation for Project for Various Scenarios

• Running Simulations– KPI Performance Prediction for different Scenarios– Coverage & Capacity Sites Identification using Heat Maps– Identification of Optimum Re-farming Strategy/Scenario– Identification of BoQ

• Spectrum Re-farming– AFP– Neighbor List

• Cell Database Parameter Optimization– Frequency plan Fine-tuning– Parametric Optimization


Parametric Optimization

Spectrum Re-farming

Running Simulations

Measurement Reports Recordings

BSS Configuration Audit & Scenarios Identification

Traffic & Coverage Heat Maps

• MaxCell’s Optimization & Analytics Modules are also tailor-made for Spectrum Re-farming related Activities– Capable of Generation of Traffic & Coverage Heat Maps based on Traffic/Trace Recordings

captured on OEMs OSS e.g. Ericsson MRR & NCS Recordings– Sophisticated Proprietary Algorithms for Generating Traffic & Coverage Heat Maps on GIS Tool – Easy Visualization– Accurately Locates Coverage Gaps– Ability to Generate Coverage Heat Maps for Various Re-farming Scenarios – Aids in Visualization of High Traffic Carrying Areas

• Use Cases– Identification of Poor Coverage Areas for Underlay/Overlay/BCCH 900/BCCH 1800– Depiction of Coverage in different Spectrum Re-farming Scenarios– New Coverage Sites Planning – Placement of Sites on GIS-Map


Coverage Heat Map Analysis

Heat Map – Existing 900 Band Underlay

Heat Map – Re-farmed Conversion of 900 Band Underlay to 1800 Band Underlay


Automatic Frequency Planning

AFP – Introduction


✓ A Multi-Vendor Automatic Frequency Planning

✓ Based on Mobile Measurement Reports Captured

✓ Improves Spectral Efficiency & Capacity

✓ Optimizes Network Performance KPIs➢ Drop Call Rate

➢ Voice Quality (RxQual)

➢ Handover Success Rate

➢ TCH Assignment Success Rate

AFP Cycle


•Configuration & Performance Data

•Site Database

•BSIC Tuning

Preparation

•Network Freeze

•MR & HO Data Collection

Traffic Recordings •Data Processing

•Model Creation & Evaluation

IM Generation

•FP Generation

•Neighbor Plan Generation

FP Iterations•FP & Neighbor Plan Download

•Overshooting/Swap Cell Correction

•Physical Optimization

Implementation

Case Studies


Case Study – Parametric Optimization (LTE)

Leading Operator - Overall LTE Pre – Post KPIs

(5 Working Days Average)

Radio Drops reduced by 15%

• Tx Power Optimization

• RS Power Optimization (Pa & Pb)

• Antenna Configuration Optimization

• Cell & Neighbor Level Parameters Tuning

• RRM Parameters

• PRACH Optimization

• UL Power Control

• PCI & Neighbor Relation Fine Tuning

• Mobility Robustness and iRAT Optimization

• Features Fine-Tuning

Performance Optimization Areas

• Radio Environment

• Maximized SINR and CQI

• Maximized Cell Edge Performance

• Improved UL Noise Rise and UL RSSI

• Key Performance Indicators

• Significant Performance Gains in following KPIs:

• Accessibility- Setup Success Rate

• Retainability- Drop Call Rate

• Handover Success Rate- Inter/Intra

• DL/UL Throughput

Gains

• Based on Live Network Performance Statistics & Traffic Recordings• Modeling the Performance at different Levels

• Per Cell• Per Carrier• Neighbor Relations – Intra & Inter RAT

• Performance Data Capture Duration• Performance Raw Statistics – 7 to 14 Days• Traffic / Trace Recordings – 3 to 5 Days

Core Optimization Concept

Summary - QoS NBH

UL RSSI reduced by 1.3 dB

Intra System HO Failure Rate reduced by 16.9%

DL Throughput increased by 11.5%

UL Throughput increased by 9.3%

Case Study – Parametric Optimization (UMTS)

• Pilot Pollution & Soft Handover Gains

• Antenna Configuration Optimization

• CPICH Power & Cell Individual Offset

• Cell & Per Neighbor Level Parameters Tuning

• RACH Optimization

• Cell Capacity

• Inter System iRAT & Inter Freq - qRxlevMin

• Soft Handovers Parameters Optimization

• Cell Coverage Shaping – Cell Individual Offsets

• Per Neighbor Relation Thresholds Setting

• reportingRange, TimeToTrigger, qOffsetxsn

• HSDPA

• Power Optimization / PDSCH Codes


• Resource Utilization

• Maximization & Optimum Usage of RF Network Resources

• CAPEX & OPEX Reduction



• RRC & RAB Setup Success Rate for CS & HSDPA

• Soft Handover Success Rate

• RAB Drop Call Rate for CS & HSDPA

• BLER Performance

• HSDPA Throughput

• Customer Experience

• Marked Improvement in KQIs

Gains


• Per Cell• Multi Carrier Level• Traffic Level

• Per Neighbor Relation• Performance Data Capture Duration

• Performance Raw Statistics – 7 to 14 Days• Traffic / Trace Recordings – 3 to 5 Days


0

0.5

1

1.5

2

2.5

RRCSetupFailureRateCS

RRCSetupFailureRatePS

RABDroppedCallRateCS

RABDroppedCallRatePS

Pre

Post

Leading Operator - Overall UMTS Pre – Post NBH KPIs (5 Working Days Average)

Significant Improvement is observed in all five KPIs

1840

1860

1880

1900

1920

1940

1960

1980

2000

2020

Pre Post

HSThroughputKbps


Case Study – Parametric Optimization (GSM)

Leading Operator - Overall GSM Pre – Post NBH KPIs

(5 Working Days Average)

The overall improvement in TCH Drop is 33%. Downlink Quality performance has also Improved and Bad Quality Samples reduced by 17%

96.50

97.00

97.50

98.00

98.50

99.00

99.50

CallComple on

Rate

HOSR GoodDLRxqual%

GoodULRxqual%

98.95

97.4497.29

97.71

99.30

97.80 97.75 97.81

Pre

Post

0.50

0.60

0.70

0.80

0.90

1.00

1.10

1.20

AverageofTCHDrop

AverageofSDDrop

1.051.11

0.70

1.07

Pre

Post

• Frequency Fine Tuning

• Optimization of ARFCN Assignment on BCCH & TCH

Layers on 10% of the Cells

• Cell & Per Neighbor Level Parameters Tuning

• Dual Band Layers – Traffic Balancing

• Handover Performance

• Handover Trigger Thresholds

• Cell Coverage Shaping – Tuning Offsets

• Per Neighbor Relation Thresholds Setting

• QoS Enhancement Features

• Activation of Features e.g. PS DL Power Control

• Repeated SAACH/FAACH


• Resource Utilization

• Maximization & Optimum Usage of RF Network Resources

• CAPEX & OPEX Reduction



• Drop Call Rate

• Handover Success Rate

• TCH Assignment Success Rate

• Good Voice Quality Samples

• Customer Experience

• Marked Improvement in KQIs

Gains


• Per Cell• Dual Band Layers• BCCH; TCH 900 & TCH 1800

• Per Neighbor Relation• Performance Data Capture Duration

• Performance Raw Statistics – 7 to 14 Days• Traffic / Trace Recordings – 3 to 5 Days


Summary - QoS NBH

Case Study 2 – Parametric Optimization (GSM)

Summary - QoS NBH & BBH

✓ Project Delivered for a Tier-1 Operator✓ Network Size- 4000+ Sites ✓ Site Configuration- 900M & 900+1800M✓ 3 Cycles of AFP and Automatic Parameter

Optimization Using MaxCell were Performed ✓ Significant Improvement Achieved in all

Major KPIs, NQI and Customer Complaints✓ Project Highlights:

✓ 28% Improvement in DLQ✓ 21% Improvement in DCR✓ 37% Improvement in Cells Meeting All

KPIs

Defaulter Cells in BBH

Case Study 2 – Parametric Optimization (GSM)

Summary- NQI & Customer Complaints

✓ Project Highlights:✓ Significant Improvement in Voice &

Data NQI✓ 142% Jump in Voice NQI✓ 37% Improvement in Cells Meeting

All KPIs ✓ 42% Jump in Overall NQI✓ 54% Reduction in Customer

Complaints Due to Radio Issues

40

Case Study – Spectrum Refarming

Summary- QoS ✓ Project Delivered for a Tier-1 Operator ✓ Refarming- 5MHz Spectrum Carved from

1800MHz✓ Network Size- 4500+ Sites ✓ Site Configuration- 900M & 900+1800M✓ Even after Spectrum Reduction Major KPIs

Were Restored to Previous Level. In Few KPIs Improvement was Achieved

✓ Project Highlights:✓ 5MHz Spectrum Carved from GSM for

LTE Deployment Without Impacting GSM Network’s Existing QoS

✓ Significant Improvement Achieved in SD Drop Rate- 12%

Case Study – AFP

Summary- QoS

✓ Project Delivered for a Tier-1 Operator✓ Network Size- 5700+ Sites ✓ Site Configuration- 900M, 1800M &

900+1800M✓ Significant Improvement Achieved in all

Major KPIs✓ Project Highlights:

✓ 75%+ Defaulting Cells Shown Improvement- DLQ and ULQ

✓ 35%+ Reduction in Defaulters DLQ✓ 28%+ Reduction in Defaulters ULQ

Defaulter Cells in BBH

Case Study – AFP

Strictly Confidential42

Significant improvement in Pre AFP DLQ Defaulter Cells▪ More than 80% defaulter Cells have shown improvement Post AFP

▪ More than 35% reduction in defaulter Cells count Post AFP

Improvement in defaulter cells in DL RxQual

Strictly Confidential43

Improvement in defaulter cells in UL RxQual

Significant improvement in Pre AFP ULQ Defaulter Cells▪ More than 79% defaulter Cells have shown improvement Post AFP

▪ More than 28% reduction in defaulter Cells count Post AFP

Case Study – AFP

KPI Name Pre (NBH) Post (NBH) Improvement (%)

TCH Drop Rate 0.91 0.7 23.08

SD Drop Rate 0.52 0.41 21.15

HO Failure Rate 2.03 1.81 10.84

TCH Assignment Failure Rate 0.5 0.41 18.00

RxQual DL – Bad (6&7) 2.98 2.16 27.52

RxQual UL – Bad (6&7) 2.32 2.05 11.64

Call Setup Failure Rate 0.81 0.68 16.05

(A) Tier 1 Operator, Asia

Network Size: GSM 8000 Cells

Scope of Work: Automatic Frequency Planning, Automatic Neighbour Planning, Overshooting Cell Correction, Swapped Sector Correction, Cell Database Parameter Optimization, QoS related Features & Functionality enabling/fine-tuning, Core Network troubleshooting, Transport Network troubleshooting.

Duration: 16 weeks

KPIs Improved:

Summary of Few Recent Projects

(B) Tier 1 Operator, Asia

KPI Name Pre (NBH) Post (NBH) Improvement (%)

RRC Setup Failure Rate CS 0.68 0.52 23.53

RRC Setup Failure Rate PS 1.44 1.29 10.42

Soft HO Failure Rate 3.62 2.45 32.32

RAB Dropped Call Rate CS 0.79 0.6 24.05

RAB Dropped Call Rate PS 2.25 1.9 15.56

Data Throughput – DL (Mbps) 18.51 20.13 8.75

Network Size: UMTS 10000 Cells

Scope of Work: Automatic PSC Planning, Automatic Neighbour Planning, Overshooting Cell Correction, Swapped Sector Correction, Cell Database Parameter Optimization, Antenna Physical Parameter Optimization

Duration: 18 weeks

KPIs Improved:

(C) Tier 1 Operator, Africa

KPI Name Pre (NBH) Post (NBH) Improvement

RRC Establishment Fail Rate 0.75% 0.67% 10.66%

e-RAB Drop Rate 1.40% 1.10% 21.42%

Handover Failure Rate 2.95% 2.25% 23.72%

Maximum Cell DL PDCP Throughput 33 Mbps 41 Mbps 24.24%

Maximum Cell UL PDCP Throughput 9.5 Mbps 10.45 Mbps 10.55%

Network Size: LTE 3500 Cells

Scope of Work: Automatic PCI Planning, Automatic Neighbour Planning, Overshooting Cell Correction, Swapped Sector Correction, Cell Database Parameter Optimization, Antenna Physical Parameter Optimization

Duration: 12 weeks

KPIs Improved:

Fracton Technologies

47

Authorized PartnerAuthorized Partner

Authorized Partner: Email: [email protected]: www.tarec-in.com

mailto:[email protected]

http://www.tarec-in.com/

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